High Levels Of Air Pollution Research Articles

Environmental regulation and firms' emission reduction – The policy of eliminating backward production capacity as a quasi-natural experiment

This study examines the effects of environmental regulations on firms' emission reductions. Using the Eliminating Backward Production Capacity policy in China as a quasi-natural experiment, our matching difference-in-differences estimation shows that the policy significantly reduces the sulfur dioxide (SO2) intensity of regulated firms by 5%. The results remain robust across different specifications and alternative outcome variables. The mechanism test results show that the reduction in SO2 intensity results from a smaller reduction in total output than in total SO2 emissions or energy consumption. This effect is particularly pronounced in regions with stronger motivation to reduce emissions, less fiscal pressure, and higher levels of air pollution, as well as in the central and western regions. Furthermore, this study finds a pollution leakage from regulated firms to other local firms. The larger the size of other local firms, the more pronounced the increase in their output. Overall, we find a 50% rebound in pollution due to leakage. However, as the policy also increases total output by 187%, our results indicate that the policy is effective in substituting backward with advanced production capacity. Our findings provide empirical evidence regarding the use of command-and-control policies to adjust the technological structure of production for technological upgrading and environmental improvement. This provides a valuable reference for developing countries to consider similar policies.

Citizen environmental complaint reporting and air quality improvement: A panel regression analysis in China

Citizen environmental complaint reporting provides a vital mode of public participation in environmental protection, particularly in addressing atmospheric pollution and improving air quality. This study explores the impact of environmental complaint reporting on the improvement of atmospheric environmental quality by employing panel regression and simultaneous equation models. Analyzing panel data from 295 Chinese cities between 2018 and 2020, The results indicate that environmental complaint reporting significantly contributes to the enhancement of atmospheric environmental quality, even after considering endogenous effects. The heterogeneity analysis results suggest that the effectiveness of environmental complaint reporting in improving atmospheric environmental quality is more pronounced in cities with higher levels of air pollution and greater economic development. In addition, the results show a differential impact of environmental complaint reporting in industrial-dominated cities compared to non-industrial cities, emphasizing their effectiveness in improving air quality among areas with more pronounced emission sources. The results of this study provide valuable insights into air pollution control efforts in China and offer important lessons for other countries facing similar challenges.

Role of Aging, Genetics after Exposure to Airborne Particulate matter and High Temperatures on a Mouse Model of Alzheimer's Disease

Background: Elevated temperatures are usually accompanied by corresponding increases in concentrations of air pollutants increasing mortality or morbidity, which may feasibly be attributed to an interaction between the two factors. High temperatures and high levels of air pollution are increasingly linked to cognitive decline in individuals over 65 years. We hypothesize that the combined exposures to particulate matter (PM2.5) and heat stress (HS) may alter brain glucose metabolism and gut dysbiosis leading to increased cognitive impairment and accelerated AD phenotype.

The synergistic health impacts of exposure to multiple stressors in Tulare County, California

Tulare County is located in the Central Valley region of California (CA). Its population is exposed to stressors that include high levels of air, water, and soil pollution, socioeconomic strain, and poor access to walkable areas and healthy foods. As a result, this population suffers from a high disease burden compared to other CA counties. We hypothesize that environmental and socioeconomic stressors interact in complex ways to raise the burden of disease in the Tulare population beyond additive impacts. We used CalEnviroScreen to select Tulare County as the subject of the study and characterized the geographical interaction of stressors. The CalEnviroScreen indicators provided the basis for population-weighted average calculations to determine the most critical environmental and socioeconomic stressors in Tulare County. We also analyzed and interpreted walkability and dietary access through open-source data. In addition, we compared disease-based mortality in Tulare County to CA state averages. Our evaluation reveals that the population living within the census tracts of Tulare County is exposed to environmental stressors at significantly higher levels relative to many other Californian census tracts, specifically for fine particulate matter, ozone, and drinking water quality. Relatively high exposures to socioeconomic stressors can compound resulting health impacts. We use dose–response curves and stressor mapping to characterize how multiple stressors may augment a population’s vulnerability and effective doses from exposure to multiple stressors. According to the Centers for Disease Control and Prevention Data, the differences in mortality rates between Tulare and CA were not significant. However, notable differences in mortality between CA and Tulare occur for Alzheimer’s disease, diseases of the circulatory system, influenza, and pneumonia, which were all statistically higher in Tulare County, and for diabetes, endocrine, nutritional and metabolic diseases, and neoplasms, which were statistically lower Tulare. Previous health-impact studies have linked individual environmental stressors to their respective measures of disease. However, many communities continue to be exposed daily to numerous stressors that individually are within regulatory limits but could significantly magnify risk due to the synergistic effects. Dose–response curves tailored to population vulnerability provide a basis for quantifying the synergistic risks of multiple stressors on specific measures of disease.

Intra-urban variability of long-term exposure to PM2.5 and NO2 in five cities in Colombia

Rapidly urbanizing cities in Latin America experience high levels of air pollution which are known risk factors for population health. However, the estimates of long-term exposure to air pollution are scarce in the region. We developed intraurban land use regression (LUR) models to map long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in the five largest cities in Colombia. We conducted air pollution measurement campaigns using gravimetric PM2.5 and passive NO2 sensors for 2 weeks during both the dry and rainy seasons in 2021 in the cities of Barranquilla, Bucaramanga, Bogotá, Cali, and Medellín, and combined these data with geospatial and meteorological variables. Annual models were developed using multivariable spatial regression models. The city annual PM2.5 mean concentrations measured ranged between 12.32 and 15.99 µg/m3 while NO2 concentrations ranged between 24.92 and 49.15 µg/m3. The PM2.5 annual models explained 82% of the variance (R2) in Medellín, 77% in Bucaramanga, 73% in Barranquilla, 70% in Cali, and 44% in Bogotá. The NO2 models explained 65% of the variance in Bucaramanga, 57% in Medellín, 44% in Cali, 40% in Bogotá, and 30% in Barranquilla. Most of the predictor variables included in the models were a combination of specific land use characteristics and roadway variables. Cross-validation suggests that PM2.5 outperformed NO2 models. The developed models can be used as exposure estimate in epidemiological studies, as input in hybrid models to improve personal exposure assessment, and for policy evaluation.

Perceived air pollution reduces consumers' self‐disclosure: The role of tense arousal

AbstractConsumers are often reluctant to disclose their personal information to retailers. How to promote consumers' self‐disclosure has been a focal point of interest for marketers and researchers. Using a total of eight multimethod studies (N = 5281) which composite a study with secondary data, a field study, a natural experiment, and five lab experiments, we show that a perception of high (vs. low) levels of air pollution decreases consumers' self‐disclosure willingness and behavior. This effect is mediated by tense arousal and moderated by (1) whether consumers are aware of the impact of perceived air pollution levels on tense arousal and (2) under which environment consumers disclose their personal information (an environment playing low‐paced soothing background music vs. a one playing high‐paced rock background music). We also rule out regulatory focus and mood valence as alternative process variables. Our findings extend past literature on perceived air pollution, tense arousal, and self‐disclosure. The results also suggest marketers, retailers, and service providers mitigate the negative impact of air pollution perception on consumers' self‐disclosure by playing low‐paced soothing background music in retailing contexts.

Using Cheaper Firewood and Paying Higher Treatment Costs in a Rural Community

Health problem related to respiratory diseases is acute particularly in rural communities where firewood and agricultural residues are used as primary fuel. The use of inefficient traditional cookstoves in poorly ventilated rooms causes high levels of household air pollution, and also contributes to ambient air pollution. Household air pollution causes significant chronic health problems such as Asthma, COPD and Heart diseases, eye pain, head, and back pain as common diseases. This study aims to investigate factor affecting human health by using firewood in inefficient stoves and estimates the associated household health costs. A field survey was administered in 3 municipalities from two districts; Sindhuli and Kavrepalanchowk districts in between the years 2019 and 2020. A survey was carried out among 221 households. To gain deeper insights, we employed a cross-sectional analytical study, utilizing primary data and applying a multiple linear regression model. The findings show that there is a positive and significant relationship between health treatment cost and firewood use. This study recommends that cook stoves programmes should not be seen as only a means to reduce deforestation and time savings, but also need to be seen from health aspects in the rural households.

Forecasting PM10 levels in Sri Lanka: A comparative analysis of machine learning models PM10

Forecasting of particulate matter (PM10) which adversely impacts air quality is highly important in ever-urbanizing cities. The relationship between particulate matter and other air quality parameters and climatic parameters is frequently investigated due to their nonlinearity. Machine learning models have been extensively used in these nonlinear predictions and showcased their ability and robustness. However, among the tested machine learning models, a comparative analysis is essential in the localized context to understand the best model that can be used to forecast future scenarios. Therefore, this research investigates the applicability of eight state-of-the-art machine learning models (ANN, Bi-LSTM, Ensemble, XGBoost, CatBoost, LightGBM, LSTM, and GRU) in the prediction of particulate matter in two urbanized areas (Battaramulla and Kandy) Sri Lanka. Regression coefficient, Root Mean Squared Error, Mean Squared Error, Mean Absolute Error, Mean Absolute Relative Error, and Nash-Sutcliffe Efficiency were incorporated to assess the best-suited model for both cities. Results revealed that the Ensemble model has the capability of accurate and precise prediction of PM10 for both cities outperforming all other models (R2≈1). Therefore, the Ensemble model is recommended for future investigation of PM10 for Sri Lanka which has a growing concern due to high air pollution levels.

Association of household solid fuel use and long-term exposure to ambient air pollution with estimated 10-year high cardiovascular disease risk among postmenopausal women

This study aimed to explore the separate and joint effects of long-term ambient air pollution and household air pollution exposure on 10-year high cardiovascular disease (CVD) risk among postmenopausal women. A total of 4679 postmenopausal women from the China Health and Retirement Longitudinal Study (CHARLS) were included in this study. Information of fuel type was collected by standard questionnaires and use of solid fuel was considered as a proxy for household air pollution. Data of ambient air pollutants (PM1, PM2.5, PM10, SO2, NO2, CO, O3) were obtained from the ChinaHighAirPollutants (CHAP) datasets. Logistic regression models were performed to assess the separate and joint effects of long-term exposure to ambient air pollution and use of solid fuel on 10-year high CVD risk. We found use of solid fuel and its duration and ambient air pollutants (PM1, PM2.5, PM10, SO2, NO2) were all positively associated with 10-year high CVD risk among postmenopausal women (P < 0.05). Compared to those used clean fuel and exposed to low ambient air pollution levels, odds ratios (ORs) and 95% confidence intervals (CIs) for participants using solid fuels and exposed to high ambient air pollution levels (PM1, PM2.5, PM10, SO2, NO2, CO, O3) were 1.66 (1.35, 2.05), 1.66 (1.35, 2.04), 1.49 (1.22, 1.83), 1.28 (1.05, 1.57), 1.67 (1.34, 2.07), 1.28 (1.04, 1.57), 1.46 (1.18, 1.80), respectively. Moreover, significant additive interactions of solid fuel use with PM1 and PM2.5 on 10-year high CVD risk were observed, with approximately 18% and 23% of 10-year high risk of CVD attributable to the interaction. Overall, indoor and outdoor air pollution had separate and joint effects on 10-year high CVD risk among postmenopausal women. Therefore, simultaneously improving indoor and outdoor air quality are of great importance and could have a joint impact on prevention of CVD and improved health among postmenopausal women.

Temporal-causal modeling of air pollution in the city of Plovdiv, Bulgaria: a case study

High levels of air pollution are dangerous to human health, which is a current problem for densely populated cities worldwide. Studying this problem can help detect pollutants’ time dependencies on basic meteorological measurements and other factors for future prediction and elaborate corresponding alarms when official upper pollution limits are exceeded. In this work, time-causal models based on previous daily time observations and meteorological measurements in the city of Plovdiv, Bulgaria, are applied. Vector-type temporal-causal models are constructed and analyzed for carbon dioxide (CO2), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine dust particles below size 10, 2.5, and 1 micron (PM10, PM2.5, and PM1), respectively. Pollution levels are predicted seven days ahead.

The influence of environmental factors on the health of the population of the Aktobe region.

This study investigates the impact of environmental factors on human health, including harmful substances, extreme temperatures, and air quality. The health status of the population in regions where many industries operate also depends on meteorological factors. The purpose of the study is to characterize and determine the influence of environmental factors (humidity, temperature, wind) and industries, including metal mining and processing regions, on the health of people in the Aktobe region, Republic of Kazakhstan. The study used general theoretical methods to analyze and systematize the results of the meteorological service of the Aktobe region and the experiments conducted by the branch of the National Centre of Expertise of the Committee of Sanitary and Epidemiological Control of the Ministry of Healthcare of the Republic of Kazakhstan for the Aktobe region in 2020 and 2021. Statistical data on the amount of chromium, lead, and nickel in the blood, and the morbidity rate of the population were analyzed. The study's findings indicate that residents in the Aktobe region experience hypothermia during winter at temperatures between -12 °C and -15 °C and humidity of 81%, and in summer overheating occurs at temperatures between +19.6 °C and +22.5 °C with humidity of 77%. These extreme temperature conditions disrupt the body's heat exchange with the environment, affecting the respiratory and circulatory systems. Moreover, the predominantly windless conditions in the region affect the atmosphere's self-cleaning ability, resulting in high levels of air pollution throughout the year. The findings can inform strategies to improve public health and prevent diseases in industrial regions. Integr Environ Assess Manag 2024;20:1156-1165. © 2023 SETAC.

Air Pollution Modeling of UNI-DEM Model by using Innovative Stochastic Approaches

In this paper we develop advanced multidimensional sensitivity analysis, based on some innovative stochastic approaches for performing air pollution modelling on a large-scale model of long-range transport of air pollutants. The Unified Danish Eulerian Model (UNI-DEM) is a very important mathematical model, and can be applied in many different studies related to damaging effects caused by high air pollution levels. We shall use it in this paper to get a reliable answer to a some very important questions regrading environmental protection. We develop some advanced Monte Carlo and quasi-Monte Carlo methods, based on special lattice and digital sequences. In this paper we will improve the digital ecosystem modeling by improving the existence stochastic approaches. The computational efficiency (in terms of relative error and computational time) of the advanced Monte Carlo algorithms for multidimensional numerical integration has been studied to analyze the sensitivity of UNI-DEM model output to variation of input emissions of the anthropogenic pollutants and of rates of several chemical reactions. The algorithms will be applied to compute global Sobol sensitivity measures corresponding to the influence of several input parameters on the concentrations of important air pollutants. The study will be done for the areas of several European cities with different geographical locations.

The synergy of ambient air quality and thermal discomfort: A case study of Greater Cairo, Egypt

The interaction between thermal discomfort and air pollution poses significant challenges for human health and environmental well-being. When there is a high level of air pollution, it can worsen thermal discomfort by trapping heat in the atmosphere. This paper aims to study this interaction in arid megacities during different weather events. Weather data and air pollution were utilized to evaluate air quality, thermal discomfort levels, their impact, and their relationship at three separate sites (Qaha, Naser City, and 6th of October City). The ambient air quality is determined by measuring the levels of particulate matter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2). The work included a statistical analysis of the discomfort index (DI) and the air quality index (AQI) for each city and their linkage with the weather. The air quality evaluation revealed that a significant portion of the population in Qaha frequently experienced discomfort and were exposed to unhealthy levels of air pollution. The results show that most of the population in all three cities experience discomfort at least some of the time with varying degrees. In Qaha, 28.97% of the population experiences no discomfort, while 25.41% experiences severe stress. In Nasr City, 32.15% of the population experiences no discomfort, while 20.21% experiences severe stress. The 6th of October City, 33.76% of the population experienced no discomfort, while 16.65% experienced severe stress. Noted that certain months, specifically June to September, are associated with higher levels of discomfort, affecting more than 50% of the population. Seasonal variations in discomfort can be due to a range of factors, including weather, climate, and environmental conditions. The temporal variation in discomfort reflects the challenges people face when transitioning from colder to hotter seasons.

On the short-term impact of pollution: The effect of PM 2.5 on emergency room visits.

In this paper, we study the short-term effect of fine particulate matter (PM 2.5) exposure on respiratory emergency room (ER) visits in Chile, a middle-income country with high levels of air pollution. To instrument for PM 2.5, we use wind speed at different altitudes (pressure levels). Unlike previous papers, our data allow us to study the impact of high pollution levels across all age groups. We find that a 1μg per cubic meter (μg/m3 ) increase in PM 2.5 exposure for 1day increases ER visits for respiratory illness by 0.36%. The effect is positive and significant for all age groups. Furthermore, the coefficients on government environmental alerts suggest that avoidance behavior becomes increasingly significant across all age groups as restrictions become more severe.

Impacts of short-term low-level exposure to air pollutants on hospital admissions for pulmonary sepsis in elderly patients

BackgroundAcute exposures to high levels of air pollutants are thought to be associated with hospitalization of patients with lung infection, while relatively little is known about the association between air pollutants and HOSPITAL ADMISSIONS FOR pulmonary sepsis.ObjectivesTo assess the correlation between low-level exposure to air pollutants and the hospitalizations for pulmonary sepsis in elderly patients.MethodsA total of 249 elderly patients with pulmonary sepsis from January 2018 to December 2020 in Shenzhen people’s hospital were included. The data regarding hospitalizations for pulmonary sepsis, meteorological factors, and daily average levels of air pollutants on single-day lags (Lag0 to Lag7) in Shenzhen were collected. Low-level exposure was defined as the annual means of air pollutants below the levels of the Ambient Air Quality Standard (AAQS) in China (NO. GB3095-2012) and/or Global Air Quality Guidelines (AQG). A time-stratified case-crossover study design approach was used to evaluate the associations between exposure to air pollutants and incidence of the disease, univariate and multivariate logistic regression analysis to analyze the association between levels of air pollutants and hospitalizations for pulmonary sepsis in elderly patients.ResultsExposure to PM1(P = 0.007, Lag 2 day; P = 0.038, Lag6 day), PM2.5(P = 0.046, Lag2 day), PM10(P = 0.048, Lag4 day), and O3(P = 0.044, Lag6 day) was positively correlated with elevated risk of hospitalizations for pulmonary sepsis. In addition, logistic regression analysis revealed that exposure to PM1 (OR = 1.833, 95%CI:1.032 ~ 3.256, Lag6 day) and O3 (OR = 2.091, 95%CI:1.019 ~ 4.289, Lag6 day) were the independent risk factors of pulmonary sepsis in elderly patients.ConclusionOur results demonstrate that short-term low-level exposure to PM1 and O3 could elevate the risk of hospitalizations for pulmonary sepsis in elderly patients in Shenzhen, providing evidence for developing early warning and screening systems for pulmonary sepsis.

Relationship between air pollutants and spontaneous abortion in a coal resource valley city: a retrospective cohort study

Objective Pollutants in the atmosphere have been linked to poor pregnancy outcomes in women. However, such investigations are scarce in metropolitan northern China. The major exposure window of air pollution affecting pregnant women is also unknown. Methods For the analysis, this retrospective cohort study enrolled 6960 pregnant women recorded at Tongchuan People’s Hospital from January 2018 to December 2019. Pollutant concentration values from the nearest monitoring station to the pregnant women were used to estimate exposure doses for each exposure window. Logistic regression models were created to investigate the connection between pollutants and spontaneous abortion while controlling for confounding factors. Results PM2.5 was a risk factor for spontaneous abortion in T3 (30–60 days before the first day of the last menstrual period [LMP]), (OR: 1.305, 95% CI: 1.143–1.490) and T4 (60–90 days before the first day of the LMP),(OR: 1.450, 95% CI: 1.239–1.696) after controlling for covariates. In the same window, PM10 was a risk factor (OR: 1.308, 95% CI: 1.140–1.500), (OR: 1.386, 95% CI: 1.184–1.621). In T2 (30 days before the first day of the LMP), T3, and T4, SO2 was a risk factor for spontaneous abortion (OR: 1.185, 95% CI: 1.025–1.371), (OR: 1.219, 95% CI: 1.071–1.396), (OR: 1.202, 95% CI: 1.040–1.389). In T3 and T4, NO2 was a risk factor (OR: 1.171, 95% CI: 1.019– 1.346), (OR: 1.443, 95% CI: 1.259–1.655). In T1 (from the first day of the LMP to the date of abortion), O3 was found to be a risk factor (OR: 1.366, 95% CI: 1.226–1.521). Conclusion Exposure to high levels of air pollutants before and during pregnancy may be a risk factor for spontaneous abortion in pregnant women. This study further illustrates the importance of reducing air pollution emissions.

Contribution of Road Transport to Pakistan’s Air Pollution in the Urban Environment

The urban areas of Pakistan exhibit some of the world’s highest levels of air pollution, primarily due to sub-2.5 μm particulate emissions. This issue significantly impairs both the country’s economy and the quality of life of its residents. Road transport is a significant contributor to anthropogenic air pollution but there are discrepancies about the extent of its share. Source apportionment and sectoral inventory studies attribute anywhere between 5 and &gt;80% of the total air pollution to vehicular sources. This uncertainty propagates into the transport policy interventions that are informed by such studies and can thus hinder the achievement of desired pollution mitigation targets. In an effort to reconcile such discrepancies and guide future studies and policy-making efforts, this paper critically reviews source apportionment studies conducted in the urban centres of Pakistan over the past two decades. The strengths and weaknesses of different approaches are compared, and results from the studies are discussed based on the emissions profile of Pakistan’s automotive fleet that emerges. Inconsistencies in the reporting of pollutant concentrations and interpreting their impacts without accounting for the relative disease burden of different pollutant species are found to be the major reasons for the large variations in the reported sectoral shares. At the end, a framework for regular air pollution monitoring and source tracking is proposed in which high-fidelity receptor-based studies inform lower-fidelity but economical sectoral inventory assessments.

OZONE-INDUCED NEUROTOXICITY: IN VITRO AND IN VIVO EVIDENCE.

Together with cities in higher-income nations, it is anticipated that the real global ozone is rising in densely populated areas of Asia and Africa. This review aims to discuss the possible neurotoxic pollutants and ozone-induced neurotoxicity: in vitro and in vivo, along with possible biomarkers to assess ozone-related oxidative stress. As a methodical and scientific strategy for hazard identification and risk characterization of human chemical exposures, toxicological risk assessment is increasingly being implemented. While traditional methods are followed by in vitro toxicology, cell culture techniques are being investigated in modern toxicology. In both human and rodent models, aging makes the olfactory circuitry vulnerable to spreading immunological responses from the periphery to the brain because it lacks the blood-brain barrier. The ozone toxicity is elusive as it shows ventral and dorsal root injury cases even in the milder dose. Its potential toxicity should be disclosed to understand further the clear mechanism insights of how it acts in cellular aspects. Human epidemiological research has confirmed the conclusions that prenatal and postnatal exposure to high levels of air pollution are linked to behavioral alterations in offspring. O3 also enhances blood circulation. It has antibacterial action, which may have an impact on the gut microbiota. It also activates immunological, anti-inflammatory, proteasome, and growth factor signaling Prolonged O3 exposure causes oxidative damage to plasma proteins and lipids and damages the structural and functional integrity of the mitochondria. Finally, various studies need to be conducted to identify the potential biomarkers associated with ozone and the brain.

Health Impacts of Environmental Inequalities in Redlined Areas

Chicago has a long history of redlining, a discriminatory housing process that has led to segregation in Chicago up to the modern day. This practice marginalized people of color and created a significant and still prevalent wealth gap between redlined and non-redlined communities. It is well known that poorer communities in Chicago are victims of negative environmental factors, such as industrial corridor proximity, and higher air pollution levels. There have been studies done on these things, but there are many overlapping factors that have led to Chicago’s prevalent inequality, creating a complex problem.&#x0D; Our study aimed to tackle some of this complexity and to analyze how various environmental indicators impacted the health outcomes of people based on the HOLC (Home Owners’ Loan Corporation) grade they lived in. We conducted a literature review to see which health impacts were tied to which significant environmental indicators and designed our technical portion to account for the complexity and inter-relation of the data, but we wanted to do more with the communities as well, rather than just analyzing data. A major part of our project was inspired by the work of Phillip Boda of UIC in regards to designing research centered around communities rather than around data. &#x0D; We came to the conclusion that the scope of our project was larger and more complex than any two people sufficiently cover and decided to design a coding tool alongside our analysis that will allow for communities to both interpret our findings and run their own analyses in the ways they deem most useful. We hope that this can both provide communities with a more thorough understanding of the complex relations between the environment and health. We also hope to provide a tool that can be more useful than existing resources we’ve used and found to have issues, such as the EPA’s Environmental Justice Screening tool (EJScreen).&#x0D; We found that higher percentages of greenlined and bluelined areas had little significance to negative health outcomes, or lowered risk, while higher percentages of red and yellowlined areas had greater significance to the model, increasing risk of negative health outcomes with increasing area. The impact of environmental indicators on our model varied depending on the health impact being analyzed, but in the case of every health impact, there was a semi-linear positive trend when a model was created taking into account all of the independent variables and their coefficients.

Changes in strontium levels in bark and over the past 40 years in the wood of trees exposed to high levels of air pollution

The present study aims to identify the most suitable tree species for monitoring and reducing strontium (Sr) pollution. Strontium is a heavy metal that is extremely harmful to human and environmental health even at low concentrations and is listed as a priority pollutant by the Agency for Toxic Substances and Disease Registry due to its potential harm. Samples were taken from Pinus pinaster, Cupressus arizonica, Picea orientalis, Cedrus atlantica, and Pseudotsuga menziesii species grown in Düzce, a location reported as one of the top 5 cities having the most polluted air in Europe by the World Air Pollution Report. The changes in Sr concentration over the last 40 years were evaluated by species, organ, direction, and age range. The results indicate that Sr pollution significantly increased due to traffic sources. This study also showed that the transfer of Sr within the wood is limited in all the species under consideration; hence, all these species can be used in monitoring the changes in Sr pollution. The most suitable species for reducing Sr pollution were Cupressus arizonica and Picea orientalis, which have the highest capacity to accumulate the most Sr in their wood.